Googles Proprietary Search Engine

Google Search Engine

Google 's Proprietary Search Engine Technology

Google 's Proprietary Search Engine Technology

Google , a highly popular search engine known for its speed and accuracy traces its beginnings to 1998 , when Stanford University Computer Science graduate students Larry Page and Sergey Brin undertook a research project . Little did they realize they will eventually devise a unique approach to solving one of the biggest challenges in the computing world - retrieving relevant information from a vast accumulation of data , or what may be more precisely described as a disorganized clutter

of database which , theless , can be navigated and scrutinized

For the founders of the company that embodied the mission "to organize the world 's information and make it universally accessible ' the spate of recognition has been unabatable . Over time , Page and Brin 's college research project would evolve into a real company offering a service that was in great demand

Google has immensely changed the computer and media landscapes over the past decade . Google today is perceived as a maverick company and one of the most disruptive forces in the business world (Weisman , 2006 br

. C5 . The impact of Google 's introduction of numerous search products , from Google Maps to Google News to Google Calendar was immense and far-reaching . The company is doing more than building its consumer base . It 's also building an alternative environment for software , advertising , and Internet content that is challenging the business models and eroding the revenue of everyone from publishers to software makers to Internet service providers (Weisman , 2006 ,

. C5

Brin and Page , in describing the anatomy of a large-scale hypertextual web search engine as part of the Computer Science Department of Stanford University in California , underscored the challenges of creating a search engine which scales even to today 's web

Fast crawling technology is needed to gather the web documents and keep them up to date . Storage space must be used efficiently to store indices and , optionally , the documents themselves . The indexing system must process hundreds of gigabytes of data efficiently . Queries must be handled quickly , at a rate of hundreds to thousands per second . These tasks are becoming increasingly difficult as the Web grows . However hardware performance and cost have improved dramatically to partially offset the difficulty . There are , however , several notable exceptions to this progress such as disk seek time and operating system robustness

Brin and Page also articulated that , aside from offering the best quality search results , Google is designed to scale . They explained

In designing Google , we have considered both the rate of growth of the Web and technological changes . Google is designed to scale well to extremely large data sets . It makes efficient use of storage space to store the index . Its data structures are optimized for fast and efficient access . In implementing Google , we have seen bottlenecks in CPU , memory access , memory capacity , disk seeks , disk throughput , disk capacity , and network IO . Google has evolved to overcome a number of these bottlenecks during various operations . Google...